The housing market was once known as the biggest money making industry in the United States. Housing, which was the way our economy made the majority of their money, is now contributing less to the economic expansion. The decline in the housing market has raised many concerns throughout the entire country. This paper provides statistics on the United States population housing market, economy, demographical characteristics, demographical area and the large amount vacant property. Included in this research document are analysis of data sets, charts and graph to help interpret the housing crisis. Research Problem

The purpose of this research is to determine why the housing market is in a downfall and if there is a way to get homeowners to see the value of their property. Many question the reason of the downfall and who does it affect. The one thing we know for sure is that the economic recession has left a big mark on society in the real estate industry. Descriptive statistics

The measures of central tendency can be measured by arithmetic mean, median and mode. The most common of the three is the arithmetic mean. Since the United States population has over one million people data collected from a large population can result in a 95% confidence level. Based on a survey done in the United States, at least three homeowner out of 1,000 are losing their homes to foreclosure. The arithmetic mean is a list of numbers which is the sum of all the members divided by the numbers on the list, we take the 1,000 homeowners divided by the approximate homeowners that are loosing their home to give us the statistical population. The median is more commonly used in situations when the mean would be influenced by extremely small and large data values. Data analysis and graphs

The median will show the frequency of the sales prices gradually increase from approximately the $80,000 range until the $250,000 to $300,000 range and then levels off. This indicates a decrease in...

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According to Trochim, “Descriptivestatistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data” (Trochim, 2006). For many years, many studies and researches have been done in real estate market. Buyers need to conduct researches to decide which house they will purchase. Buyers’ concerns include the price of the house, the number of bedrooms, and location. Real estate agents need to gather all the necessary information to provide their services to buyers. Additionally, the agents must be able to predict what types of houses are most likely to sell. In this paper, I will provide the summary of what I have been studying. The paper will include the measure of central tendency, dispersion, and skew for data. In addition, this paper will also contain graphic data as well as tabular data to demonstrate my findings and studies. In the end, conclusion will present whether my research findings answered the problem statement or if more research may be needed.
Examining the data collected for the current real estate market desires, following are the conclusions based on its findings. There are many key...

...DescriptiveStatistics: Real Estate
University of Phoenix
RES/341 Research and Evaluation I
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Does having a pool increase the price of houses that have the same number of bedroom? In order to answer that question, we divided our data set into two groups; houses with 1 to 3 bedrooms and houses with 4 and more bedrooms. We then compared the prices of houses with a pool to houses without a pool in each group. Different calculations were used to determine the central tendency, dispersion, and the skew of our data. The central tendency helps to simplify data and also to predict future results. We can use diverse calculations to measure it such as the mean, mode, and median. According to our sample of houses with 1 to 3 bedrooms, the mean price was higher of $4,060 for houses without a pool than with a pool. The same rule applies to houses with more than 4 bedrooms, but with a larger difference of $51,170. Another way we used to calculate the central tendency is by finding the median. The medians are also higher in each group for houses without a pool than those with a pool.
To better answer the above question, we also analyzed the skewness of our data in the two groups. . If we look at the two groups, houses with 1 to 3 bedrooms and houses with 4 or more bedrooms, the data seems to be skewed to the right because the mean is larger than the median. However, due to the...

...DescriptiveStatisticspaper
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The information below is a continuance of week two, week three, and on week four. The previous assessment in week two on “real estate research” for thinking of hypothesis on home values in Alvarado, Texas. The evaluating on real estate prices reveals a purpose of this research paper and its importance findings. The discoveries include problem definition, and on variables.
The next assessment was on week three on “data collection” on reviewing literatures, sampling design, and on any ethical concerns with collection data on the same topic. A summary was assembled in week three on terms of population, sampling size, and factors on real estate. This research found house prices to change in each different region.
This is week four paper on “descriptivestatistics” on real estate in Alvarado, Texas. The information below will consist of; data analysis, data using graphic and tabular techniques, and on skew values, histogram measures, and on central tendency.
The Central tendency is the measures of numerical summaries used to summarize data with a one number. The most common used are mode, mean, and median. The Hypothesis is "homes more or less expensive fifteen miles away from the center of the city"? The comparison will come from the City of...

...Running head: DESCRIPTIVESTATISTICSPAPERDescriptiveStatisticsPaper
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Few sports have had the social impact that baseball has had over the years. Baseball has long been the all-American pastime. Baseball parks in most major cities across the U.S. attract families including children with dreams of becoming a baseball player. Although ballpark attendance is near 75 million, the cost to operate a major league team is substantial. Salaries alone for 2005 were over 2 billion (University of Phoenix, 2004). This number has increased nearly five-fold over the previous 10 years (USA Today, 2008). People pay to see the best athletes in all sports, not just baseball. Baseball owners analyze data to determine if paying their players higher salaries will pay off by increasing the attendance in ballparks. The data collected in the Major League Baseball Data set is typical data which owners will analyze to determine if paying higher salaries will increase overall profitability.
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The purpose of this research is to determine whether or not increasing the budget for player salaries will increase the attendance in ballparks. Baseball is not unlike any other business where the name...

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Whether doing original research or conducting literature reviews, one must conclude what a powerful and versatile tool statistics are in the hands of researchers. From basic statistics such as data description, to using complex statistical methods to foresee future patterns or strengthen scientific claims about current climates, the role of statistics in research cannot be taken lightly and is essential in almost any field, especially in psychology. The statistical method is divided into two main branches called descriptive and inferential statistics. Descriptivestatistics is a summary of information and the data presented is easily understood. Inferential statistics are much more detailed and are used to draw conclusions about hypotheses or determine probabilities of an outcome. Both allow researchers to describe, graph and present data for a general audience or more technical for the professionals. Without statistics, researchers lose that vital tool that allows them to move from hypothesis to conclusion.
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By
September 27, 2010
In this paper Team B will examine the data that we have collected and we will draw a conclusion based on your findings, to get to the conclusion we will analyze the data using descriptivestatistics, we will calculate the measures of central tendency, and dispersion, we will also show all the information with graphics and tables for a better understanding of the date, after all these steps are executed we will draw our conclusion.
Data Analysis Using DescriptiveStatistics
Through this paper, Team B will use the philosophy of descriptivestatistics to describe the main feature of the collection of data quantitatively (Main PS 1995). Descriptivestatistics will provide simple summaries about the samples and the measures. In essence, we will show a summary of the data that the team has collected. Some of the ways that we will show the data collected will be in the form of first central tendency which is the distribution locates the center of a distribution of values. The three types of the central tendency are the mean, the median and the mode. Secondly, we will look at the dispersion which is the spread of values around the central tendency (Dodge 2003). The standard deviation is a more accurate way of measuring the dispersion....

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Statistics
BUS308: Statistics for Mangers
Instructor:
Learning Statistics
Statistical data has become an item that we see all around us in our everyday lives, from television programs talking about selling products or politicians using data to show how they perform in their jobs, in hopes to be reelected. Throughout the course in Statistics for Managers, I have learned many things on how the use of statistical information can help me to understand these items and also to help me to perform my job and understand the day-to-day operation of the company. With the use of statistics, anyone can find out information and details on most anything, allowing them to understand a business better or to make better decisions in their everyday life. Because statistics is all around us, using and understanding this information is important to find answers to questions, to make better decisions, and understand how things work.
Some of the types of information I have learned to use is through the use of descriptive and inferential statistics. According to the textbook for statistics, “descriptive characteristics can provide a great economy when data sets are large. Inferential statistics are utilized when the sample’s characteristics are important for what they reveal about the entire population”. (Tanner & Youssef-Morgan,...

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In research, the need to accurately produce results is imperative to efficient research. Team C’s hypothesis of what generates champion teams needs many tools provided in research to achieve a true answer. Team C has further simplified the meaning of champion team to any team whose team dynamics cause the team to have a winning season. With that being said, this paper will be focused on the research tools needed and the results provided by the tools to answer what stats are important for teams in the MLB to win games and eventually be champions.
Measures of Central Tendencies
Even when dealing with enormous sets of data it is important to get an idea by looking at the measures of central tendency. The first three that will be looked at are mean, median, and mode. Mean is “a measure of central tendency that offers a general picture of data without inundating one with each of the observations in a data set” (Sekaran, p. 396, para 3). A more common term for mean is average. The median is “the central item in a group of observations when they are arrayed in ascending or descending order” (Sekaran, p. 396, para 5). Mode is the “most frequently occurring phenomenon” (Sekaran, 396, para 6). The following table shows the mean, median, and mode for the four sets of data that Team C will be researching:...